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Iolo Jones

2 accepted papers

2026

Carré du champ flow matching: better quality-generalisation tradeoff in generative models

ICLR 2026poster

Deep generative models often face a fundamental tradeoff: high sample quality can come at the cost of memorisation, where the model reproduces training data rather than generalising across the underlying data geometry. We introduce Carré du champ flow matching (CDC-FM), a generalisation of flow matc…

Cited by 0SourceScholar
2026

Riemannian Metric Matching for Scalable Geometric Modeling of Distributions

ICML 2026oral

High-dimensional datasets often concentrate near low-dimensional structures, but estimating their geometry from samples typically relies on graphs and kernels that scale poorly with dataset size and dimension. We propose **Riemannian metric matching**: a denoising probabilistic framework for learnin…

Cited by 0SourceScholar